class_docstr: A running estimate of performance (operations/sec) using adjusted exponential moving average
  :param alpha: Smoothing factor in range [0, 1], [default: 0.1].
code: def __init__(
      self, alpha: float = 0.1, eps: float = 1e-20, paused: bool = False
  ):
      self.alpha, self.eps, self.num_updates = alpha, eps, 0
      self.ema_seconds_per_sample, self.samples_per_second = 0, eps
      self.timestamp = time.perf_counter()
      self.paused = paused
      self.lock = Lock()
  
file_path: hivemind/hivemind/utils/performance_ema.py
imports: import time
  from contextlib import contextmanager
  from threading import Lock
  from typing import Optional
label_desc: Use image node_id 1 to create a new PerformanceEMA object  with example: obj = PerformanceEMA(alpha, eps, paused)